Construction and Handling of CVST.data Objects
The CVST methods needs a structured interface to both regression and classification data sets. These helper methods allow the construction and consistence handling of these types of data sets.
constructData(x, y) getN(data) getSubset(data, subset) getX(data, subset = NULL) shuffleData(data) isClassification(data) isRegression(data)
x |
The feature data as vector or matrix. |
y |
The observed values (regressands/labels) as list, vector or factor. |
data |
A |
subset |
A index set. |
constructData
returns a CVST.data
object. getN
returns the number of data points in the data set. getSubset
returns a subset of the data as a CVST.data
object, while
getX
just return the feature data. shuffleData
returns a
randomly shuffled instance of the data.
Tammo Krueger <tammokrueger@googlemail.com>
nsine = noisySine(10) isClassification(nsine) isRegression(nsine) getN(nsine) getX(nsine) nsineShuffeled = shuffleData(nsine) getX(nsineShuffeled) getSubset(nsineShuffeled, 1:3)
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